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Channel

❂ 𝓽𝓰 𝓼𝓱𝓸𝓹(通知频道)

@huafugx

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

3,246subscribers

-142 since we began measuring on 13 September 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001706232304
TypeChannel
Username@huafugx
Created12 July 2022 — measured — dated from the channel’s first post
First recorded13 September 2026
Last confirmed live6 October 2026
Measurements held6
Confirmed unchanged1 time, most recently 6 October 2026
On Telegramt.me/huafugx

Topic

Marketing & affiliate — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 29 September 2026 and assigned it the closest of 31 fixed categories, at 79% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Growth

3,2463,3883,31713 September 2026 — 3,388 subscribers13 September 2026 — 3,388 subscribers14 September 2026 — 3,380 subscribers19 September 2026 — 3,334 subscribers29 September 2026 — 3,269 subscribers6 October 2026 — 3,246 subscribers13 September 20266 October 2026
6 measurements spanning 23 days, net -142. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 3,225–3,409 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
6 Oct 2026, 08:553,246-23
29 Sept 2026, 04:383,269-65
19 Sept 2026, 03:393,334-46
14 Sept 2026, 08:563,380-8
13 Sept 2026, 16:223,388no change
13 Sept 2026, 15:473,388first reading

Engagement

19 posts held, back to 12 July 2022 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 19 posts for this entry, the most recent from 27 August 2026. An engagement rate over an empty window would be a number about nothing.

What this channel posts

Video runtime
1m 59s
Average length
1m 59s

Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.

Reaction mix

5,409 reactions across 7 posts, in 11 distinct kinds. The most used accounts for 15.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤81015.0%
👍81015.0%
🔥77414.3%
🎉76614.2%
😁4929.10%
🥰3927.25%
💯3276.05%
😍3266.03%
🤩3235.97%
❤‍🔥3095.71%
👏801.48%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 8 of the 19 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 5,409 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 19 most recent posts we hold, published 12 July 2022 to 27 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

27 Aug 2026, 11:11 UTC389 viewsread 13 September 2026

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14 Aug 2026, 19:20 UTC619 viewsread 13 September 2026
Photo

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13 Aug 2026, 14:02 UTC481 viewsread 13 September 2026
Photo

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12 Aug 2026, 13:23 UTC711 views1 reactionsread 13 September 2026
Photo

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❤1

11 Aug 2026, 23:26 UTC412 viewsread 13 September 2026

美国SEC将自行处理加密货币监管事宜 币界网消息,美国证券交易委员会(SEC)在 Clarity Act法案上周未能在美国国会通过后,决定将自行处理加密货币监管

10 Aug 2026, 21:21 UTC457 viewsread 13 September 2026

2026年8月12日的日全食可见地区主要集中在以下区域: 全食带: - 格陵兰岛东北部 - 冰岛西部 - 西班牙北部(包括巴伦西亚、毕尔巴鄂等城市) - 葡萄牙东北端极小部分地区 - 北冰洋沿岸俄罗斯区域 日偏食地区: - 欧洲大部分地区 - 加拿大大部分地区 - 美国北部(从阿拉斯加到北卡罗来纳州) - 非洲西北部 需要注意的是,中国地区不在本次全食带内,无法观测到日全食,但全国大部分地区可以看到不同程度的日偏食,越靠近北方地区遮挡效果越明显 。

10 Aug 2026, 12:28 UTC444 viewsread 13 September 2026

日本央行行长植田暗示9月加息促成美日联合买入日元 币界网消息,据日本共同社报道,多位日本政府官员透露,日美两国政府于7月31日实施了一次联合日元买入干预,这是28年来首次此类行动。日本央行行长植田和男在记者会上暗示,将在9月及之后尽早提高政策利率,并表示如有必要将“加快加息步伐”。美方对此给予积极评价,双方在阻止日元过度贬值方面步调一致。美国担忧日本加息迟缓导致日元贬值,引发物价上涨和长期利率攀升,可能波及全球金融市场。

9 Aug 2026, 15:31 UTC439 viewsread 13 September 2026

日本金融厅成立专门的加密和稳定币部门 币界网消息,日本金融服务局(FSA)正式成立专门的加密和稳定币部门。该机构将加密监管从办公室级别提升为独立部门,并设立三个子单位,分别负责交易所监测、创新和数字支付。这一举措是日本金融工具与交易法(FIEA)改革的后续,重新将比特币、以太坊及其他103种代币重新分类为金融工具。

23 Jul 2026, 15:46 UTC≈1,380 views0 reactionsread 13 September 2026
Photo

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17 Jul 2026, 08:06 UTC≈1,460 views1 reactionsread 13 September 2026

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❤1

Showing the 12 most recent of 19 posts we hold for @huafugx. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 6 October 2026 — this entry's latest reading, not the date you are reading this.

“❂ 𝓽𝓰 𝓼𝓱𝓸𝓹(通知频道)” (@huafugx), 3,246 subscribers as measured 6 October 2026. Telegram Register, tgregister.com/channel/huafugx.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.